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改变标准设计的两种随机化测试程序的I型错误率和功率
1Department of Social Psychology and Quantitative Psychology, Faculty of Psychology, University of Barcelona, Passeig de la Vall d'Hebron 171, 08035, Barcelona, Spain. rrumenov13@ub.edu.
随机化试验为分析单个案例实验设计 (SCED) 提供了强大的方法,特别是改变标准设计. 这项研究表明,这些测试可以控制错误率,并通过足够的数据点实现足够的统计能力.
科学领域:
- 行为科学 行为科学
- 心理学 心理学 心理学
- 研究方法研究方法研究方法学
背景情况:
- 单个案例实验设计 (SCED) 对于评估各种领域的干预措施至关重要.
- 随机化测试是分析SCED数据的具有历史意义和统计学上的有效方法.
- 改变标准设计,一种特定类型的SCED,在随机化测试分析方面得到的关注较少.
研究的目的:
- 评估改变标准设计的两种随机化程序的I型错误率和统计能力.
- 为了研究诸如序列长度,相数,自相关性和随机变量的因素对测试性能的影响.
- 为实施这些随机化测试提供实际指导和R代码.
主要方法:
- 模拟研究估计I型错误率和统计能力.
- 研究了两个随机化程序:相变时刻随机化和阻断交替标准随机化.
- 各种参数包括序列长度,相数,自相关度水平和随机变量.
主要成果:
- 在模拟条件下,I型错误率通常得到了很好的控制.
- 通过大约28-30次独立数据测量,可以获得足够的统计能力.
- 观察到具有积极自相关性的更高功率,并且对以前的标准的逆转是有益的.
结论:
- 随机化测试是改变标准设计的可行和有效的分析方法.
- 充足功率所需的测量次数受数据特征的影响,特别是自相关性.
- 提供的R代码有助于在实践中应用这些方法.
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